Research Scientist
Phare Health
United States
USD 140k-300k / year + Equity
Posted on Nov 20, 2025
About Phare & R1
Phare is building healthcare’s first Revenue Operating System - a platform that uses AI to make hospital billing and reimbursement effortless, accurate, and fair. We recently became part of R1, one of the largest companies managing healthcare claims which serves hundreds of systems around the country. This gives us the best of both worlds: the DNA of an AI startup paired with the scale of a healthcare organization that supports care delivery for hundreds of healthcare systems nationwide. Join us on our mission to build a fairer, faster model for healthcare payments.
The Role
We skew toward the RS/RE blend – applied scientists who feel comfortable getting close to production code. You’ll conduct applied research on real healthcare data, focused on explainability, reinforcement learning, and long-context information retrieval. You’ll move quickly from concept to deployment - designing experiments, training models at scale, and collaborating with MLOps and product teams to turn ideas into measurable user impact. You’ll stay close to the literature and close to production, coding your own experiments end to end.
This is an in-person role in NYC requiring at least 3 days in the SoHo office.
About You
You have a PhD in computer science / informatics plus at least 3 years of industry experience (will consider postdocs also). You have:
Phare is building healthcare’s first Revenue Operating System - a platform that uses AI to make hospital billing and reimbursement effortless, accurate, and fair. We recently became part of R1, one of the largest companies managing healthcare claims which serves hundreds of systems around the country. This gives us the best of both worlds: the DNA of an AI startup paired with the scale of a healthcare organization that supports care delivery for hundreds of healthcare systems nationwide. Join us on our mission to build a fairer, faster model for healthcare payments.
The Role
We skew toward the RS/RE blend – applied scientists who feel comfortable getting close to production code. You’ll conduct applied research on real healthcare data, focused on explainability, reinforcement learning, and long-context information retrieval. You’ll move quickly from concept to deployment - designing experiments, training models at scale, and collaborating with MLOps and product teams to turn ideas into measurable user impact. You’ll stay close to the literature and close to production, coding your own experiments end to end.
This is an in-person role in NYC requiring at least 3 days in the SoHo office.
About You
You have a PhD in computer science / informatics plus at least 3 years of industry experience (will consider postdocs also). You have:
- Experience designing novel architectures and pipelines in PyTorch/TensorFlow/JAX - strong preference for applied research which has made its way into production.
- Research expertise in one or more of: interpretability, reinforcement learning, retrieval-augmented generation, or long-context information retrieval.
- Comfortable running large-scale training and evaluation on distributed infrastructure (e.g., Ray, FSDP, Lightning).
- Track record publications at top ML venues (e.g., NeurIPS, ICML, EMNLP, MLHC, CHIL).
- Top-of-market compensation (salary + equity)
- Flexible PTO
- Hybrid in-office (min. 3 days per week)
- Comprehensive health benefits
- 401(k) matching
- Inspiring, brilliant, mission-driven teammates
- Intro call - your background & our mission alignment
- Technical deep-dives - pseudo-coding exercise and systems design (not Leetcode)
- Culture interview in person in NYC
- References
- Offer